ArticleBritish journal of pharmacology2013
PKPD modelling of the interrelationship between mean arterial BP, cardiac output and total peripheral resistance in conscious rats.
Article in British journal of pharmacology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Inter-study variability of preclinical in vivo safety studies and translational exposure-QTc relationships--a PKPD meta-analysis.British journal of pharmacology · 2015Pooled it
- Modelling hemodynamics regulation in rats and dogs to facilitate drugs safety risk assessment.Frontiers in pharmacology · 2024Article
- Evaluation of a Cardiovascular Systems Model for Design and Analysis of Hemodynamic Safety Studies.Pharmaceutics · 2023Article
- A novel cardiovascular systems model to quantify drugs effects on the inter-relationship between contractility and other hemodynamic variables.CPT: pharmacometrics & systems pharmacology · 2022Article
- Semi-mechanistic modelling platform to assess cardiac contractility and haemodynamics in preclinical cardiovascular safety profiling of new molecular entities.British journal of pharmacology · 2020Article
- Quantitative pharmacokinetic-pharmacodynamic modelling of baclofen-mediated cardiovascular effects using BP and heart rate in rats.British journal of pharmacology · 2016Article
- Modeling and Simulation Approaches for Cardiovascular Function and Their Role in Safety Assessment.CPT: pharmacometrics & systems pharmacology · 2015Review
- Drug effects on the CVS in conscious rats: separating cardiac output into heart rate and stroke volume using PKPD modelling.British journal of pharmacology · 2014Article
- The 24 h pattern of arterial pressure in mice is determined mainly by heart rate-driven variation in cardiac output.Physiological reports · 2014Article
Corrections and comments
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Authors and funding
11 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and purposeThe homeostatic control of arterial BP is well understood with changes in BP resulting from changes in cardiac output (CO) and/or total peripheral resistance (TPR). A mechanism-based and quantitative analysis of drug effects on this interrelationship could provide a basis for the prediction of drug effects on BP. Hence, we aimed to develop a mechanism-based pharmacokinetic-pharmacodynamic (PKPD) model in rats that could be used to characterize the effects of cardiovascular drugs with different mechanisms of action (MoA) on the interrelationship between BP, CO and TPR. EXPERIMENTAL APPROACH: The cardiovascular effects of six drugs with diverse MoA, (amlodipine, fasudil, enalapril, propranolol, hydrochlorothiazide and prazosin) were characterized in spontaneously hypertensive rats. The rats were chronically instrumented with ascending aortic flow probes and/or aortic catheters/radiotransmitters for continuous recording of CO and/or BP. Data were analysed in conjunction with independent information on the time course of drug concentration using a mechanism-based PKPD modelling approach. KEY
resultsBy simultaneous analysis of the effects of six different compounds, the dynamics of the interrelationship between BP, CO and TPR were quantified. System-specific parameters could be distinguished from drug-specific parameters indicating that the model developed is drug-independent. CONCLUSIONS AND IMPLICATIONS: A system-specific model characterizing the interrelationship between BP, CO and TPR was obtained, which can be used to quantify and predict the cardiovascular effects of a drug and to elucidate the MoA for novel compounds. Ultimately, the proposed PKPD model could be used to predict the effects of a particular drug on BP in humans based on preclinical data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.